Runpod Blog.

Join Runpod CEO Zhen Lu and Data Science Dojo CEO Raja Iqbal on October 11 for a live fireside chat about GPU-powered AI transformation and the future of scalable machine learning infrastructure.

This guide breaks down everything you need to know about billing on RunPod—how credits are applied, what gets charged, and how to set up automatic or manual funding.

Runpod partners with RandomSeed to power easy-to-use API access for Stable Diffusion through AUTOMATIC1111, making generative art more accessible to developers.

Runpod has partnered with Data Science Dojo to power their Large Language Model bootcamps, providing scalable GPU infrastructure to support hands-on learning in generative AI, embeddings, orchestration frameworks, and deployment.

Runpod introduces new Serverless pricing with Flex and Active worker types, offering better scalability and up to 40% lower costs for consistent workloads.

Falcon-180B is the largest open-source LLM to date, requiring 400GB of VRAM to run unquantized. This post explores how to deploy it on Runpod with A100s, L40s, and quantized alternatives like GGUF for more accessible use.

Klangio uses AI to transcribe music from recordings into readable notation, empowering learners and professionals alike. With Runpod’s infrastructure, Klangio can scale without the burden of managing GPU infrastructure.